A System for Human Identification From X-Ray Dental Radiographs

2003

Forensic dentistry involves the identiÿcation of people based on their dental records, mainly available as radiograph images. Our goal is to automate this process using image processing and pattern recognition techniques. Given a postmortem radiograph, we search a database of antemortem radiographs in order to retrieve the closest match with respect to some salient features. In this paper, we use the contours of the teeth as the feature for matching. A semi-automatic contour extraction method is used to address the problem of fuzzy tooth contours caused by the poor image quality. The proposed method involves three stages: radiograph segmentation, pixel classiÿcation and contour matching. A probabilistic model is used to describe the distribution of object pixels in the image. Results of retrievals on a database of over 100 images are encouraging.

Dental features have been widely used for forensic identification purposes. With the large number of cases that need to be investigated by forensic odontologists, a move towards computer-aided dental identification systems is necessary. We propse an automated scoring and ranking method that can be used to augment other text-based methods such as WinID. Given a postmortem (PM) radiograph with a marked region of interest (ROI), we search the database of antemortem (AM) radiographs to retrieve a closest match. To express the degree of similarity/overlap between two radiographs, we use the weighted sum of squared differences (SSD) cost function. The method was tested on a database of 571 radiographs belonging to 41 distinct individuals. In 90% of the identification trials, our method ranked the correct match in the top 10%. In all trials, the correct match was among the top 22%. These experiments indicate that matching dental records using the SSD cost function is a viable method for human dental identification.

Dental features have been widely used for forensic identification purposes. With the large number of cases that need to be investigated by forensic odontologists, a move towards computer-aided dental identification systems is necessary. We propse an automated scoring and ranking method that can be used to augment other text-based methods such as WinID. Given a postmortem (PM) radiograph with a marked region of interest (ROI), we search the database of antemortem (AM) radiographs to retrieve a closest match. To express the degree of similarity/overlap between two radiographs, we use the weighted sum of squared differences (SSD) cost function. The method was tested on a database of 571 radiographs belonging to 41 distinct individuals. In 90% of the identification trials, our method ranked the correct match in the top 10%. In all trials, the correct match was among the top 22%. These experiments indicate that matching dental records using the SSD cost function is a viable method for human dental identification.

Journal of Electronic Imaging, 2005

Forensic odontology has long been carried out by forensic experts of law enforcement agencies for postmortem identification. We address the problem of developing an automated system for postmortem identification using dental records (dental radiographs). This automated dental identification system (ADIS) can be used by law enforcement agencies as well as military agencies throughout the United States to locate missing persons using databases of dental x rays of human remains and dental scans of missing or wanted persons. Currently, this search and identification process is carried out manually, which makes it very time-consuming in mass disasters. We propose a novel architecture for ADIS, define the functionality of its components, and describe the techniques used in realizing these components. We also present the performance of each of these components using a database of dental images.

RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, 2018

Purpose In forensic odontology the comparison between antemortem and postmortem panoramic radiographs (PRs) is a reliable method for person identification. The purpose of this study was to improve and automate identification of unknown people by comparison between antemortem and postmortem PR using computer vision. Materials and Methods The study includes 43 467 PRs from 24 545 patients (46 % females/54 % males). All PRs were filtered and evaluated with Matlab R2014b including the toolboxes image processing and computer vision system. The matching process used the SURF feature to find the corresponding points between two PRs (unknown person and database entry) out of the whole database. Results From 40 randomly selected persons, 34 persons (85 %) could be reliably identified by corresponding PR matching points between an already existing scan in the database and the most recent PR. The systematic matching yielded a maximum of 259 points for a successful identification between two di...

Journal of Indian Academy of Oral Medicine and Radiology, 2011

Automated dental identification system is computer-aided software for the postmortem identification of deceased individuals based on dental characteristics specifically radiographs. This system is receiving increased attention because of the large number of victims encountered in the mass disasters and it is 90% more time saving and accurate than the conventional radiographic methods. This technique is based on the intensity of the overall region of tooth image and therefore it does not necessitate the presence of sharp boundary between the teeth. It provides automated search and matching capabilities for digitized radiographs and photographic dental images and compares the teeth present in multiple digitized dental records in order to access their similarity. This paper highlights the functionality of its components and techniques used in realizing these components.

2003 46th Midwest Symposium on Circuits and Systems, 2003

Law enforcement agencies have been exploiting biometric identifiers for decades as key tools in forensic identification. A biometric identifier has to resist the early decay that affects body tissues. Because of their survivability and diversity, the best candidates for postmortem biometric identification are the dental features.

2016

Forensic dentistry involves the identification of humans based on their dental records, mainly based on dental radiographs/photographs. The method developed, deals with identification of human using dental information. Many works in this field proves that it is possible for identifying humans from dental radiograph records, matching antemortem and post-mortem data. This method is used in the time of disasters causing mass loss of human life. In those cases when other biometric data may be missing or cannot be used, dental data is considered for forensics. The proposed method deals with identification of human from dental photographs and radiographs, since radiographs may not be available always. A semi-automated algorithm for matching teeth from available photographic and radiographic images is implemented. In this research, intensity features are used for matching. In the case of photographs, homomorphic filtering is used to normalize the brightness across the image and to increase...

Regular, 2020

Dental radiographs do a great deal of work on the evidence of criminal classification. Science deontology is used in crimes that deal with the evidence of a person's separation related to dental exposure. Due to the advances in data design and the need to evaluate more cases by legal professionals, it is important to use a human evidence framework. Dental radiographs can be classified as biometric if there are no alternatives to body biometrics, for example, palm, finger, iris, face, leg print, and so on. The human body seen using dental radiographs is best under certain conditions when there are no biometric alternatives because the teeth and bones are treated like skin tissues and tissues found in the human body.

Journal of Digital Imaging, 2020

Due to the damage to biometric properties in the event of natural disasters, like fire or earthquakes, it is very difficult to identify human remains. As teeth are more durable than other biometric properties, identifying information obtained from them is much more reliable. Therefore, in cases where alternative biometric properties cannot be obtained or used, information taken from teeth may be used to identify a person's remains. In recent years, many studies have shown how the identification process, previously performed manually by a forensic dental specialist, can be made faster and more reliable with the assistance of computers and technology. In these studies, the x-ray image is subdivided into meaningful parts, including jaws and teeth, and dental properties are extracted and matched. In order to extract the features accurately and ensure better matching, it is important to segment images properly. In this study, (i) lower and upper jaw and (ii) tooth separation was performed to segment panoramic dental x-ray images to assist in identifying human remains. To separate the jaws, a novel meta-heuristic optimization-based model is proposed. To separate teeth, a user-assisted, semi-automatic approach is presented. The proposed methods have been performed with a computer program. The results of the implementation of these methods of jaw and tooth separation in panoramic tooth images are encouraging.